Individuals, enterprises, and corporations are continually exposed to the risk of future events beyond their control which can either positively or negatively impact their financial stability. A corporation's financial stability is expressed in terms of yearly profit, the primary financial metric for many of its publicly available performance indicators. These indicators, including earnings per share, net income, and income growth are important to the success of a corporation because investors look to these indicators to assess whether to invest in the corporation. If the indicators are positive and indicate growth, investors are more likely to invest in the corporation. Therefore, it is important for a corporation to limit events that could negatively impact these indicators.
Risk can take many forms in view of the variety of future events that may occur. For example, some types of risk concern technical phenomena—the breakdown of a power plant, aircraft engine failure, or the damage to, or failure of, orbiting telecommunications satellites.
Another type of risk is economic in nature. Examples include fluctuation of commodity prices, currency exchange rates, interest rates, property prices, share prices, inflation rates, and market event based indices. Economic risk, also known as price risk, is the primary concern of financial markets.
Financial markets measure risk in terms of volatility, which is commonly defined as a statistical measure of the tendency of a market, security, or derivative to rise or fall sharply within a given period of time. If the tendency is for a security to rise or fall very sharply, the security is said to be highly volatile.
Volatility is an important component in the valuation of many financial derivatives. For example, when determining the value of an option, volatility is used as an independent variable that denotes the extent which the return of the underlying asset (e.g., stock prices) will fluctuate between the initial date of the option and its expiration date. In this way, volatility is an essential element when determining the level of option prices. If volatility is high, the premium (i.e., cost to purchase) on the option will be relatively high, and vice versa. Once you have a reliable measure of statistical volatility for any underlying asset, the fair market value of an option is calculable by utilizing a standard options pricing model.
However, the task of determining the volatility of a given financial instrument is not straightforward. As a result, many methods have been developed, and these methods vary greatly in their design, assumptions and results. Often management of various risks is performed using arcane technical language that varies from one functional area to another.
Normally a corporation delegates the responsibility of risk management to a risk manager, who considers the issues of probability and severity separately. Accordingly, sufficient data to accurately determine a volatility function is rarely available making it extremely difficult for organizations to place consistent valuations on associated risks, and to subsequently determine how to most accurately optimize the allocation of resources across an entire enterprise.
As a result, resources are allocated based upon either historical happenstance (i.e. the organization is aware of a recent large loss that increases its sensitivity to the risk associated with a particular hazard) or the organizational ability of the manager (i.e. the manager gathers more resources within the organization).
Some risk managers utilize more subjective ranking systems to order the relative severity, probability and control costs. Labels may be associated to each outcome indicating a subjective valuation of the severity and probability. For example severity may be ranked with labels such as “high,” “medium,” or “low.” Probability may be ranked with labels such as “certain,” “likely”, “unlikely,” or “rarely.” The cost to control the risk can similarly be ranked as “high”, “moderate” or “low”. Certain ranking methodologies purport to apply equally to all risks in an organization, but do not establish consistent operational definitions and measurement methodologies across the various functional areas. “High” and “likely” labels indicate different levels of risk to different individuals. Existing methodologies do not recognize the interdependencies that exist between various risk controls, nor do they answer the question of whether economic value is being created by risk control efforts. In addition, quantifying risk in a subjective manner can lead to widely disparate results. Consequently, subjective ranking is often used as a screening method to determine relevant data sources.
After identifying likely volatile sources, risk managers generally attempt to mitigate the adverse consequences associated with that volatility. A traditional, well known mitigation method is the purchasing of insurance. Insurance is the simple transfer of risk from one party, the insuree, to another party, the insurer in exchange for the payment of a fixed premium price. Purchasing insurance to mitigate has several advantages. First, large entities with considerable experience with insuring a particular type of risk can often accurately predict the probability of loss, which enables insurers to set fairly accurate pricing. Second, insurers are able to pool risks by creating a large, diversified portfolio of policies. That is, by issuing a large number of insurance policies, an insurer can diversify its risk and reduce premiums to the consumer.
However, there are several disadvantages to using insurance as a risk management tool. While an insurer may accurately predict the probability and amount of loss, the administrative expenses associated with maintaining the accuracy of these functions are high. Also, insurance companies must deal with adverse selection because an insurer often cannot differentiate between a risk that never occurs and an event insured against which actually happens. Finally, insurers must deal with the “moral hazard.” That is, once a risk has been insured, the insurer must be concerned that the insuree may exercise less careful to protect against the risk that may occur.
To compensate for the disadvantages, insurers must transfer some of the additional risk to the insuree by raising premium costs. As a result, the cost to protect against a given risk is often higher than it would be without the need to protect the insurer's additional risk. Of course, if the costs associated with managing risk by purchasing insurance outweigh the protections provided by the insurance, risk managers would be loath to purchase it. As a result, insurance is inherently an imperfect risk management system.
An alternative risk management tool is a process known as hedging, wherein parties exchange derivative instruments in order to offset the price risk associated with fluctuations in cash markets.
Many entities including commercial firms, consumers, and producers utilize a hedging technique to protect themselves from price risk. Hedging enables a party to transfer risk to another party because the parties leverage related products and services which respond similarly to the same economic factors. This leverage of related products and/or services is known as correlation.
An entity can use any of several derivatives in the hedging process. The simplest of such derivatives is known as a forward contract, which is a transaction wherein a buyer and a seller agree upon price and quantity for delivery of a specific service or commodity at a future point in time. While such a forward contract transfers risk, there are disadvantages to utilizing it as a risk management tool. For example, forward contracts are not standardized, so each transaction must be negotiated individually. In addition, while such forward contracts are legally binding, upon default a party must resort to the legal system for recovery. As a result of theses disadvantages, transaction costs associated with negotiating, maintaining and enforcing forward contracts are often unnecessarily high. Therefore, forward contracts are generally inefficient risk management tools.
Of course, in an attempt to compensate for the inefficiencies associated with variable-term forward contracts, they can be standardized as to include specific terms. Standardized forward contracts are known as futures contracts and are generally standardized with respect to quantity, time, and place for delivery of goods and services. Because futures contracts are standardized, an entity can theoretically purchase and sell futures contracts without ever actually taking physical delivery of the subject of the contract.
To eliminate the need for legal enforcement of a forward contract, a margin system was created to prevent buyers and sellers from defaulting on their contract. In a margin system, the buyer and the seller of a futures contract deposit cash to a margin account maintained by a third party, usually an exchange or a bank, as collateral to guarantee performance of the futures contract. In addition, a margin may be “marked-to-market,” whereby the amount of money deposited into a margin account is updated continuously as the price of the underlying derivative fluctuates.
Since the terms of a futures contract are standardized and delivery need not ever be completed, a properly executed contract is all that is required for buying, selling, and trading the contract, making the process fairly liquid. To improve the liquidity of this process, exchanges were formed to facilitate these transactions on a larger scale. Currently, exchanges are the preferred forum for trading futures contracts because risk managers appreciate the benefits of standardized features.
Futures options are analogous to futures contracts. The difference between the two is the fact that with futures options a party is not actually obliged to actually accept delivery of the underlying commodity. Instead, a party has the right to refuse delivery. The result is that unlike futures contracts, futures options are not subject to margin calls (i.e., the instrument is not marked to market unless a party actually takes delivery) and have lower potential risk. There are disadvantages to purchasing a futures option. For example, because one party has the right to refuse delivery of the futures option, the futures option is more expensive to purchase that a futures contract. The higher price negatively impacts the return of the instrument, resulting in a lower yield. Because the yield is lower, it is a more inefficient risk management tool than a standardized futures contract.
Typical buyers and sellers of derivative instruments have a vested interest in the fluctuation of price rates and attempt to manage their risk accordingly. Alternatively, certain buyers or sellers (e.g., a speculator) can purchase the instrument without having a vested interest in the fluctuation of prices. A speculator will purchase or sell a futures instrument when he or she believes feels that he or she can predict what will happen with a particular price risk more accurately than the market.
Speculators are generally parties who purchase a derivative such that they will experience financial gain when the price fluctuation of the derivative is actually higher than an expected threshold, or sell a derivative such that they will experience financial gain when the price fluctuation of the derivative is lower than expected.
For example, consider a wheat farmer who wishes to sell his upcoming harvest. While prices for his crop remain steady, the farmer is worried that the value of his crops at harvest time will drop. The farmer (seller) can agree to deliver his wheat at harvest time to a miller, (buyer), who is worried that the price of wheat will increase between the contract date and the harvest (delivery) date. The farmer and the miller have both attempted to manage the risk of the commodity, namely wheat. Note that if the price of wheat rises, the miller is said to gain value because the contract was executed at a lower price. Conversely, if the price of wheat falls, the farmer gains value because the contract was executed at a premium over the price the farmer could have obtained.
The same principles hold for intangible financial products and services. For example, consider an entity that holds a contract to sell a product in a foreign market that will be paid for in foreign currency. If the foreign currency increases in value relative to the domestic currency, it will convert into less domestic currency. To protect itself against this currency risk, the domestic entity can buy a foreign currency futures contract. Similar to the farmer/miller example, if the foreign currency appreciates, the loss on conversion on the initial contract is offset by the increased value of the futures contract. As a result, hedging is the preferred method of managing risk regarding price risks associated with currency fluctuation.
Although there are numerous benefits to hedging, risk managers do not currently hedge against every contingency. To determine if a risk management strategy is needed, risk managers generally utilize a simple cost-benefit analysis. If the risk that needs to be hedged has only a small impact on an entity's business it may decide that hedging against that risk is unnecessary. Similarly, if the exposure is minimal, risk managers may be unwilling to invest limited resources to hedge. As a result, a company typically only hedges large expenditures and/or commodities that substantially impact the bottom line due to their underlying volatility.
For example, consider an entity that has a large exposure to inflation. To manage this risk the entity can purchase and/or trade a Consumer Price Index (CPI) future. The CPI index is a measure of inflation based on publicly available information. Since almost every entity is exposed to inflation related price risk there is a large market for buyers and sellers who wish to manage this risk and the CPI index market trades at a high volume. While it can be generally utilized effectively to hedge short-term changes in inflation, and the index price is stable because it is based on government-published historic data, because it is a new type of futures contract the total number of contracts available is limited. In addition, the CPI index is not an accurate measure of the volatility of uncorrelated products and services (e.g., healthcare) because uncorrelated products and services increase in price at a different rate than inflation.
By way of example, healthcare costs in the United States are presently increasing at two to three times the rate of inflation and at four times the rate of wage increases. In an attempt to measure the increase in healthcare costs, entities rely on the healtcare trend, which indicates the percentage increase of healthcare expenditures per capita over a predetermined period of time. The components of the healthcare trend are highly variable, making the healthcare trend extremely volatile. For instance, general inflation, consumer demand, government regulation, drug costs, unit cost, seasonality, and annual fluctuations in severity of variable illness, all of which are exemplary components of the healthcare trend, are very volatile. Therefore entities that attempt to manage health related expenditures have difficulty budgeting and forecasting these costs due to this volatility, which affects the entity's bottom line. Because of the direct impact of sharply rising healthcare costs on an entity's financial stability, managing the price risk of healthcare related costs is vital.
For example, a Fortune 100 company like General Motors has high financial exposure to such risk factors as currency risk, credit risk from its financing division, interest rate risk from its financing division, and fuel cost risk from the sale of automobiles. These financial risks are correlated to significant sources of revenue from (or significant expenditures related to), automobile products and services. General Motors therefore hedges against these risks in one form or another utilizing financial derivative instruments.
In 2003, General Motors (GM) spent $4.8 billion on healthcare for its employees, which constituted an expenditure greater that its expenditure for steel. Because healthcare costs comprise a large percentage of General Motor's expenditures, one would expect it to manage its healthcare risk by utilizing financial derivatives. However, because there is no reliable method for managing its healthcare risk in this manner, General Motors does not manage healthcare risk using financial derivatives. Instead, it relies on other risk management techniques.
Presently, the only viable method of managing the risk associated with healthcare costs is for an entity to purchase health insurance. The insurance premiums associated with such insurance have been rising at an alarming rate due to increasing costs that reflect the inherent variability of the healthcare industry, such as the cost of prescription drugs. As a result, the present system for managing risk associated with healthcare costs (i.e., health insurance) is inefficient.
As premium costs continue to rise, insurance companies presently offer a variety of insurance types in an attempt to manage price risk and volatility of healthcare expenditures.
One type of the insurance now offered is a method of reducing healthcare costs known as stop-loss insurance.
Stop-loss insurance is purchased by self insured employers in an attempt to stabilize their healthcare costs. While a typical self insured employer can predict the approximate number of doctor visits its employees will have in a given year, it cannot predict the number of “catastrophic events” (e.g., premature births, cancer, and organ transplants) that will occur in a given year. The costs associated with these procedures can be devastatingly high to a self insurer so there exists a need to hedge against this type of risk.
There are two main types of stop-loss insurance. The first is known as Individual Stop Loss “ISL,” sometimes called Specific Stop Loss. Individual Stop Loss protects an employer against expenditures by single individuals which exceed a predetermined dollar limit chosen by the employer. For example, if an employee of the insured incurs injuries in an accident that requires expenditures that far exceed the premium's stated deductible, the ISL insurance would reimburse the employer for all associated expenses beyond a predetermined dollar amount.
The second type of stop-loss insurance is known as Aggregate Stop Loss (ASL), or Excess Risk Insurance. Aggregate Stop loss insures an employer against the total expenditures by its employees as compared to a predetermined dollar amount. An employer typically purchases ASL to cover against 125% of the level of expected claims predicted by the insurance carrier. For example, a mid sized self insurer with $4 million in expected claims could purchase a stop loss policy that initiates when $5 million in claims are incurred.
Despite the obvious advantages associated with the various types of stop loss insurance, there are numerous disadvantages. For example, conservative pricing and limited availability of stop loss insurance policies severely curtails the usefulness of stop loss insurance to small health plans with limited financial resources. In contrast, large companies can afford the costs associated with a few catastrophic claims, so the steep cost of stop loss insurance becomes economically wasteful. Consequently, stop loss insurance is limited to mid-sized self insured employers because such entities often do not have large enough cash reserves or generate enough income to cover the costs associated with several catastrophic claims. In addition, stop loss insurance solutions maintain extreme volatility because typical stop loss plans do not take effect until the incurred claims exceed a 25% threshold.
Because current healthcare risk management techniques have limited success and sharply rising healthcare costs continue to impact an entity's financial stability, there is a clear need in the art for a system and method to more effectively manage the risk associated with healthcare costs. The present invention overcomes the various deficiencies associated with traditional healthcare risk management techniques by creating a novel healthcare index and associated financial derivative instrument that allows risk managers to effectively and efficiently hedge the highly volatile fluctuations associated with predicting healthcare costs.